Abstract
In this paper, we describe blur identification and restoration of noisy degraded images. The point-spread function (PSF) can be characterized by the quantity of blur. Thus the blur identification problem can be solved as a parameter estimation problem. The estimation method is a generalized cross-validation (GCV) criterion that is known as a powerful measure that can be used to choose the optimal regularization parameter without a priori knowledge about noise. We use the iterative damped-1east squares (DLS) algorithm which is based on the principle of damped least-squares for restoring noisy degraded images.
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Ishizaka, T., Maeda, J. Blur identification and restoration of degraded images using generalized cross-validation criterion. Optical Review 1, 202–204 (1994). https://doi.org/10.1007/BF03254862
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DOI: https://doi.org/10.1007/BF03254862